• Corpus ID: 219531127

AdaLAM: Revisiting Handcrafted Outlier Detection

@article{Cavalli2020AdaLAMRH,
  title={AdaLAM: Revisiting Handcrafted Outlier Detection},
  author={Luca Cavalli and Viktor Larsson and Martin R. Oswald and Torsten Sattler and Marc Pollefeys},
  journal={ArXiv},
  year={2020},
  volume={abs/2006.04250}
}
Local feature matching is a critical component of many computer vision pipelines, including among others Structure-from-Motion, SLAM, and Visual Localization. However, due to limitations in the descriptors, raw matches are often contaminated by a majority of outliers. As a result, outlier detection is a fundamental problem in computer vision, and a wide range of approaches have been proposed over the last decades. In this paper we revisit handcrafted approaches to outlier filtering. Based on… 

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